Multi-objective optimization to support mission planning for constellations of unmanned aerial systems

2008 ◽  
Author(s):  
S. Tenenbaum ◽  
D. Stouch ◽  
K. McGraw ◽  
T. Fichtl
Keyword(s):  
Mission Planning ◽  
Unmanned Aerial Systems ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Aerial Systems

Risk assessment in mission planning of uninhabited aerial vehicles

2019 ◽  
Vol 233 (10) ◽  
pp. 3499-3518 ◽  
Author(s):  
Giulio Avanzini ◽  
David S Martínez
Keyword(s):  
Initial Conditions ◽  
Mission Planning ◽  
Unmanned Aerial Systems ◽  
Steady State Condition ◽  
Motion Primitives ◽  
Uninhabited Aerial Vehicles ◽  
Aerial Systems ◽  
The Impact ◽  
Navigation Errors ◽  
Time Of Failure

A procedure for evaluating the risk related to the use of unmanned aerial systems over populated areas is proposed. A nominal trajectory, planned for performing a given mission, is represented by means of motion primitives, that is segments and arcs flown in a steady-state condition. The risk of hitting a person on the ground after catastrophic failure is evaluated as a function of vehicle reliability and population density (assumed known), and position of the impact point (which depends on initial conditions at the time of failure and trajectory flown afterwards). In the deterministic case, a lethal area is introduced and the risk at each point on the ground is proportional to the amount of time spent by the point inside the lethal area. Under the assumptions of a ballistic fall, the position of the lethal area with respect to the nominal trajectory depends only on altitude and velocity at the time of failure. When the effect of navigation errors is introduced, impact points are described by a statistical impact footprint, assuming that position and velocity errors at time of failure are normally distributed with known standard deviations. The two approaches are compared for a fictitious, yet realistic, mission scenario.

Multi-objective optimization of space station short-term mission planning

2015 ◽  
Vol 58 (12) ◽  
pp. 2169-2185 ◽  
Author(s):  
HuiJiao Bu ◽  
Jin Zhang ◽  
YaZhong Luo ◽  
JianPing Zhou
Keyword(s):  
Space Station ◽  
Mission Planning ◽  
Multi Objective Optimization ◽  
Short Term ◽  
Multi Objective

scholarly journals Design and Development Autonomous Unmanned Aerial Vehicle Software

2020 ◽  
Vol 9 (4) ◽  
pp. 2105-2108
Keyword(s):  
Autonomous Navigation ◽  
Application Programming Interface ◽  
Detection Algorithm ◽  
Mission Planning ◽  
Unmanned Aerial Systems ◽  
Localization And Mapping ◽  
Wide Range ◽  
Human Operators ◽  
Emergency Scenarios ◽  
Aerial Systems

Unmanned aerial vehicles are the cutting edge technology which is used in various arduous applications and emergency scenarios. But human operators find it burdensome and experience a lot of physical and mental stress while operating the aerial systems in critical and emergency scenarios such as rescue operations, mine inspection, and surveillance. Our proposed idea is to provide the autonomous capability and features to these automatons by developing a mission-planning application that can autonomously guide UAV operations even in GPS denied environments by implementing SLAM (Simultaneous Localization and Mapping). With autonomous capability, aerial systems can help to plummet the stress on human operators or may even perform the process or mission efficiently without human intervention in numerous applications. Applications involving autonomous unmanned aerial systems have increased in recent times and are being applied in a wide range of fields such as infrastructure, transport, agriculture, mining, media, and transport. This paper covers the working of the autonomous navigation algorithm, artificially intelligent object detection algorithm and the mission planning API (Application Programming Interface).

scholarly journals A SATELLITE IMAGING MISSION PLANNING METHOD FOR FAST ANTARCTICA COVERAGE

2020 ◽  
Vol V-4-2020 ◽  
pp. 217-222
Author(s):  
Y. Chen ◽  
X. Shen ◽  
G. Zhang ◽  
T. Liu ◽  
Z. Lu ◽  
...  
Keyword(s):  
Time Window ◽  
Time Windows ◽  
Ice Sheet ◽  
Planning Method ◽  
Mission Planning ◽  
Multi Objective Optimization ◽  
Antarctic Ice Sheet ◽  
Satellite Imaging ◽  
Multi Objective ◽  
Imaging Time

Abstract. Global warming has become one of the most prominent global issues, and Antarctic ice sheet is one of the indicator of global climate change. Satellite imagery has become an important means of monitoring the changes in Antarctic ice sheet. Due to the high overlap of satellite imaging swaths, the existing Antarctica images have the disadvantages of long period of imagery acquisition, large temporal difference among the mosaic images, and low utilization of satellite resource. This paper proposes a satellite imaging mission planning method for fast Antarctica coverage. First, the imaging time window is forecasted within the specified imaging time range to obtain all the visible time windows of the imaging satellite to Antarctica. Then, taking the selection of each time window and the satellite swing angle in each time window as decision variables, and the satellite attitude maneuver ability as constraint, an imaging mission model including two objective functions with minimum number of imaging time windows and the maximum coverage rate is established. To solving the proposed multi-objective optimization model, an improved real-binary hybrid LMOCSO (large-scale multi-objective optimization based on a competitive swarm optimizer) is proposed in this paper. Finally, a simulation experiment was performed using Gaofen-3 satellite to verify the effectiveness of the proposed method.

scholarly journals A Mission Planning Approach for Precision Farming Systems Based on Multi-Objective Optimization

Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1795 ◽  
Author(s):  
Zhaoyu Zhai ◽  
José-Fernán Martínez Ortega ◽  
Néstor Lucas Martínez ◽  
Jesús Rodríguez-Molina
Keyword(s):  
Farming Systems ◽  
Precision Farming ◽  
Mission Planning ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Planning Approach
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